Structured pruning for deep convolutional neural networks: A survey
The remarkable performance of deep Convolutional neural networks (CNNs) is generally
attributed to their deeper and wider architectures, which can come with significant …
attributed to their deeper and wider architectures, which can come with significant …
Drone navigation using region and edge exploitation-based deep CNN
Drones are unmanned aerial vehicles (UAV) utilized for a broad range of functions,
including delivery, aerial surveillance, traffic monitoring, architecture monitoring, and even …
including delivery, aerial surveillance, traffic monitoring, architecture monitoring, and even …
Noninvasive blood glucose monitoring using spatiotemporal ECG and PPG feature fusion and weight-based choquet integral multimodel approach
J Li, J Ma, OM Omisore, Y Liu, H Tang… - … on Neural Networks …, 2023 - ieeexplore.ieee.org
change of blood glucose (BG) level stimulates the autonomic nervous system leading to
variation in both human's electrocardiogram (ECG) and photoplethysmogram (PPG). In this …
variation in both human's electrocardiogram (ECG) and photoplethysmogram (PPG). In this …
Feature independent Filter Pruning by Successive Layers analysis
Convolutional neural networks (CNNs) have become deeper and wider over time. However
due to low computational power, mobile devices or embedded systems cannot use very …
due to low computational power, mobile devices or embedded systems cannot use very …
Global probability distribution structure-sparsity filter pruning for edge fault diagnosis in resource constrained wireless sensor networks
C Zhao, B Tang, L Deng, Y Huang, H Tan - Engineering Applications of …, 2024 - Elsevier
In this paper, a global probability distribution structure-sparsity filter pruning is proposed to
address the problem of difficult deployment of diagnostic models in resource constrained …
address the problem of difficult deployment of diagnostic models in resource constrained …
An Effective Information Theoretic Framework for Channel Pruning
Y Chen, Z Wang - arXiv preprint arXiv:2408.16772, 2024 - arxiv.org
Channel pruning is a promising method for accelerating and compressing convolutional
neural networks. However, current pruning algorithms still remain unsolved problems that …
neural networks. However, current pruning algorithms still remain unsolved problems that …
Class-Separation Preserving Pruning for Deep Neural Networks
Neural network pruning has been deemed essential in the deployment of deep neural
networks on resource-constrained edge devices, greatly reducing the number of network …
networks on resource-constrained edge devices, greatly reducing the number of network …
Structure-Preserving Network Compression Via Low-Rank Induced Training Through Linear Layers Composition
Deep Neural Networks (DNNs) have achieved remarkable success in addressing many
previously unsolvable tasks. However, the storage and computational requirements …
previously unsolvable tasks. However, the storage and computational requirements …
[PDF][PDF] CICC: Channel Pruning via the Concentration of Information and Contributions of Channels.
Channel pruning provides a promising prospect to compress and accelerate convolutional
neural networks. However, existing pruning methods neglect the compression sensitivity of …
neural networks. However, existing pruning methods neglect the compression sensitivity of …
Structure-Preserving Network Compression Via Low-Rank Induced Training Through Linear Layers Composition
I Alkhouri, X Zhang, R Wang - Transactions on Machine Learning Research - openreview.net
Deep Neural Networks (DNNs) have achieved remarkable success in addressing many
previously unsolvable tasks. However, the storage and computational requirements …
previously unsolvable tasks. However, the storage and computational requirements …